A method and system for mine ecological restoration planning based on 3D modeling

Abstract

This invention relates to the field of mine ecological restoration and 3D modeling technology, specifically a mine ecological restoration planning method and system based on 3D modeling. The method includes: acquiring a basic spatial dataset of the mine to construct a mutation-driven dynamic 3D model layer; generating a sampled change sequence along the route, constructing a minimum disruptive unit object and generating a mutation event object; extracting sampled change fragments along the route and performing structured aggregation to generate a feasibility evidence package, generating a minimum intervention action kernel object; based on the local intervention verification loop within the segment of the minimum disruptive unit object, performing local verification on the minimum intervention action kernel object to determine the elimination status of the mutation event object, and outputting a verification result set; updating the feasibility status of the minimum disruptive unit object and the mutation event object to generate a mine ecological restoration planning scheme. This invention realizes a feasible mine ecological restoration planning method based on mutation-driven dynamic 3D modeling.

Description

Technical Field

[0001] This invention relates to the field of mine ecological restoration and 3D modeling technology, specifically to a mine ecological restoration planning method and system based on 3D modeling. Background Technology

[0002] In the process of mine ecological restoration planning, it is usually necessary to conduct a systematic analysis of the topography, engineering facilities and surrounding environment of abandoned mines to determine the layout schemes for engineering projects such as roads, drainage, slope treatment and landscape restoration. With the development of 3D modeling technologies such as UAV real-scene modeling, point cloud reconstruction and digital elevation models, mine governance design, linear engineering route selection and visibility analysis based on 3D models have become common technical means. In existing technologies, 3D modeling methods are mainly used to geometrically reconstruct and visualize the existing topography of mines. In the planning stage, indicators such as slope, length and elevation changes are calculated based on the 3D model to generate planning schemes for mine ecological restoration and supporting projects. When conducting ecological restoration planning in abandoned mines and designing and laying out linear engineering projects such as roads and drainage based on 3D models, there is still a systematic deviation between the 3D modeling results and the actual feasibility of the linear engineering. Specifically, this includes: First, when using existing 3D modeling results for terrain analysis, they often focus on reflecting the overall slope and undulation. For minor subsidence, short-distance reverse slopes, and undulating steps along a route that is only one or two meters long but could directly cause water accumulation, backflow, or construction failure during actual construction, it is difficult to identify them clearly and promptly in the model. This leads to routes that appear to meet continuous downhill or slope control requirements in the 3D model experiencing local failures during on-site implementation. Second, when generating ecological restoration and linear engineering planning schemes based on the aforementioned 3D models, when there are local sections in the route that cannot be satisfied by simply adjusting the alignment or slope parameters, existing planning methods usually only allow for overall route rerouting or temporary remedies based on human experience. It is difficult to directly formulate a scheme that addresses only the local section at the planning stage, resulting in repeated modifications to the planning scheme during implementation and frequent rework during the construction phase. Summary of the Invention

[0003] The purpose of this invention is to provide a mine ecological restoration planning method and system based on three-dimensional modeling, so as to solve the problem of systematic deviation between the three-dimensional modeling results and the actual feasibility of linear engineering mentioned in the background art.

[0004] To achieve the above objectives, the technical solution of the present invention is: a mine ecological restoration planning method based on three-dimensional modeling, comprising: S1. Obtain the basic dataset of mine space and construct a three-dimensional terrain surface model. Load the linear engineering planning constraint set into the three-dimensional terrain surface model and establish the engineering constraint interaction relationship. Based on the three-dimensional terrain surface model and the linear engineering planning constraint set, construct a mutation-dominated dynamic three-dimensional model layer. S2. Based on the engineering constraint relationship and along the engineering corridor direction, generate the sampling change sequence along the line in the mutation-dominated dynamic three-dimensional model layer. Compare and analyze the sampling change sequence along the line with the engineering constraint relationship to construct the minimum destruction unit object, and generate the mutation event object corresponding to the minimum destruction unit object. Write the minimum destruction unit object and the mutation event object into the mutation-dominated dynamic three-dimensional model layer. In S2, the minimum destruction unit object is a segment unit divided along the engineering corridor direction to characterize the local terrain constraint state; the mutation event object is an event identifier object in the minimum destruction unit object that indicates an engineering constraint violation. S3. Extract the sampled change segments along the line located by the mutation event object from the mutation-dominated dynamic 3D model layer, and structure and collect the sampled change segments along the line to generate a feasibility evidence package. Combine the linear engineering planning constraint set to generate a minimum intervention action kernel object that corresponds one-to-one with the minimum destruction unit object. Based on the local intervention verification loop within the segment of the minimum destruction unit object, perform local verification on the minimum intervention action kernel object to determine the elimination status of the mutation event object, and output the verification result set. In S3, the minimum intervention action kernel object is a set of intervention actions used to eliminate the corresponding mutation event object within the segment range of the minimum destruction unit object; the local intervention verification loop is a verification path limited to the segment range of the minimum destruction unit object. S4. Write back the kernel object of the minimum intervention action corresponding to the verification result set to the mutation-dominated dynamic three-dimensional model layer, and update the feasibility status of the minimum destruction unit object and the mutation event object; based on the updated mutation-dominated dynamic three-dimensional model layer, parametrically reconstruct the linear engineering planning constraint set to obtain the linear engineering planning dataset, so as to generate a mine ecological restoration planning scheme.

[0005] Preferably, in S1, the mutation-dominated dynamic 3D model layer is constructed based on a 3D terrain surface model and superimposed with engineering constraint relationships. It is used to carry a 3D model layer that associates multiple engineering state evolution information under a unified 3D spatial benchmark. The mutation-dominated dynamic 3D model layer includes: a 3D terrain surface model constructed from a mine spatial basic dataset, engineering constraint relationships formed by loading a linear engineering planning constraint set, and minimum destruction unit objects and mutation event objects. Among them, the minimum destruction unit objects are mapped onto the 3D terrain surface model in the form of segments, and the mutation event objects are associated with the corresponding minimum destruction unit objects. This is used to represent the local engineering constraint state and its change results in the mutation-dominated dynamic 3D model layer.

[0006] Preferably, in step S2, the along-line sampling change sequence is a terrain change data sequence obtained by continuously sampling the three-dimensional terrain surface model in the mutation-dominated dynamic three-dimensional model layer based on the engineering constraint relationship and along the engineering corridor direction. It is used to characterize the continuous change state of the terrain spatial morphology in the engineering corridor direction, and is also used to compare and analyze with the engineering constraint relationship to identify the changes in the local engineering constraint state, so as to construct the minimum destruction unit object. The minimum destruction unit object is a segment unit divided along the engineering corridor direction, used to carry the engineering constraint state within the corresponding segment. The data structure of the minimum destruction unit object includes a segment spatial identifier, a along-line sampling change sequence fragment corresponding to the segment, and a segment engineering constraint state field.

[0007] Preferably, in step S2, the mutation event object is an event identifier object generated based on the constraint violation correspondence between the minimum disruptive unit object and the linear engineering planning constraint set, used to characterize the local engineering mutation situation in which engineering constraint violation occurs in the minimum disruptive unit object; the data structure of the mutation event object includes the corresponding minimum disruptive unit object identifier, the engineering constraint violation type identifier, and the mutation status field; the specific method for constructing the mutation event object is as follows: for each minimum disruptive unit object, determine whether the sampling change sequence along the line in its corresponding segment violates the constraint conditions in the linear engineering planning constraint set, and generate a mutation event object that is bound one-to-one with the minimum disruptive unit object when there is a constraint violation.

[0008] Preferably, in step S3, the sampled change segment along the line is a sequence segment extracted from the sampled change sequence along the line that is consistent with the spatial identifier of the smallest destruction unit object segment corresponding to the mutation event object; the feasibility evidence package is a data set formed by structuring and aggregating the sampled change segments along the line according to the engineering constraint violation type of the mutation event object, used to represent the spatial morphological characteristics and constraint status information of the engineering constraint violation within the corresponding smallest destruction unit object segment; the method of structuring and aggregating the sampled change segments along the line to generate the feasibility evidence package is as follows: based on the engineering constraint violation type recorded in the mutation event object, extract the change sequence field corresponding to the constraint violation type from the sampled change segments along the line, and encapsulate the extracted change sequence field together with the segment spatial identifier and the engineering constraint violation type identifier to generate a feasibility evidence package that corresponds one-to-one with the mutation event object.

[0009] Preferably, in S3, the minimum intervention action kernel object is a set of intervention action parameters generated for mutation event objects within the segment of the minimum destruction unit object, used to limit the engineering intervention actions to be performed within the segment; the method for generating the minimum intervention action kernel object by combining the sampled change fragment along the line with the linear engineering planning constraint set is as follows: based on the sampled change fragment along the line and the engineering constraint violation type recorded in the feasibility evidence package, the constraint condition parameters corresponding to the engineering constraint violation type in the linear engineering planning constraint set are extracted, and an intervention action parameter set corresponding to the constraint condition parameters is generated within the segment spatial identifier limit of the minimum destruction unit object, thereby forming a minimum intervention action kernel object that corresponds one-to-one with the minimum destruction unit object.

[0010] Preferably, in S3, the local intervention verification loop is a verification processing path limited to the range of action of the minimum disruptive unit object segment, used to verify the constraint satisfaction of the minimum intervention action kernel object in the corresponding segment; the elimination status of the mutation event object is a status identifier used to characterize whether the corresponding mutation event object still has an engineering constraint violation; the method for performing local verification of the minimum intervention action kernel object to determine the elimination status of the mutation event object is as follows: within the range of the segment spatial identifier of the minimum disruptive unit object, the intervention action parameters corresponding to the minimum intervention action kernel object are applied to the sampled change segment along the line, and the constraint status of the applied segment is re-determined according to the linear engineering planning constraint set. When the determination result shows that there is no longer an engineering constraint violation in the corresponding segment, the elimination status identifier of the mutation event object is generated.

[0011] Preferably, in step S4, writing back the minimum intervention action kernel object corresponding to the verification result set to the mutation-dominated dynamic 3D model layer specifically involves: writing the minimum intervention action kernel object whose elimination state is satisfied in the verification result set into the mutation-dominated dynamic 3D model layer, and updating the segment engineering constraint state field of the corresponding minimum destruction unit object and the mutation state field of the mutation event object; based on the updated mutation-dominated dynamic 3D model layer, performing parameterized reconstruction processing on the linear engineering planning constraint set, specifically involves: within the range of action of the minimum destruction unit object segment, mapping the intervention action parameters corresponding to the written minimum intervention action kernel object to the engineering constraint parameter adjustment amount, and forming an engineering parameterized adjustment result that corresponds one-to-one with the segment spatial identifier, thereby generating a linear engineering planning dataset.

[0012] On the other hand, the present invention provides a mine ecological restoration planning system based on three-dimensional modeling, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the above-described mine ecological restoration planning method based on three-dimensional modeling.

[0013] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial technical effects: 1. In this invention, based on the mutation-driven dynamic three-dimensional model layer and the section-level object-oriented modeling mechanism, it is possible to directly identify and express short-distance reverse slope, micro-settlement and local constraint mutation problems that are difficult to find in traditional models in the three-dimensional modeling stage. This allows the planning basis to no longer remain at the level of overall slope or macro-topography, but to be implemented at the level of constructable sections, thus avoiding planning deviations where the model is feasible but the site is not. 2. In this invention, a parameterized planning generation mechanism consisting of the minimum destructive unit object, the minimum intervention action kernel object, and the local intervention verification loop is used to achieve point-to-point repair and parameter-level adjustment of local problem sections. Without the need for overall rerouting or repeated manual correction, an implementable linear engineering planning dataset is directly generated, thereby significantly reducing the risk of repeated planning modifications and construction rework, and improving the certainty and feasibility of mine ecological restoration planning. Attached Figure Description

[0014] Figure 1 This is a flowchart of one embodiment of the present invention. Detailed Implementation

[0015] Example 1, as Figure 1 As shown, the specific implementation steps of the mine ecological restoration planning method based on three-dimensional modeling proposed in this invention are as follows: S1. Obtain the basic dataset of mine space and construct a three-dimensional terrain surface model. Load the linear engineering planning constraint set into the three-dimensional terrain surface model and establish the engineering constraint interaction relationship. Based on the three-dimensional terrain surface model and the linear engineering planning constraint set, construct a mutation-dominated dynamic three-dimensional model layer. S2. Based on the engineering constraint relationship and along the engineering corridor direction, generate the sampling change sequence along the line in the mutation-dominated dynamic three-dimensional model layer. Compare and analyze the sampling change sequence along the line with the engineering constraint relationship to construct the minimum destruction unit object, and generate the mutation event object corresponding to the minimum destruction unit object. Write the minimum destruction unit object and the mutation event object into the mutation-dominated dynamic three-dimensional model layer. In S2, the minimum destruction unit object is a segment unit divided along the engineering corridor direction to characterize the local terrain constraint state; the mutation event object is an event identifier object in the minimum destruction unit object that indicates an engineering constraint violation. S3. Extract the sampled change segments along the line located by the mutation event object from the mutation-dominated dynamic 3D model layer, and structure and collect the sampled change segments along the line to generate a feasibility evidence package. Combine the linear engineering planning constraint set to generate a minimum intervention action kernel object that corresponds one-to-one with the minimum destruction unit object. Based on the local intervention verification loop within the segment of the minimum destruction unit object, perform local verification on the minimum intervention action kernel object to determine the elimination status of the mutation event object, and output the verification result set. In S3, the minimum intervention action kernel object is a set of intervention actions used to eliminate the corresponding mutation event object within the segment range of the minimum destruction unit object; the local intervention verification loop is a verification path limited to the segment range of the minimum destruction unit object. S4. Write back the kernel object of the minimum intervention action corresponding to the verification result set to the mutation-dominated dynamic three-dimensional model layer, and update the feasibility status of the minimum destruction unit object and the mutation event object; based on the updated mutation-dominated dynamic three-dimensional model layer, parametrically reconstruct the linear engineering planning constraint set to obtain the linear engineering planning dataset, so as to generate a mine ecological restoration planning scheme.

[0016] In this embodiment S1, the mine spatial basic dataset is a set of basic data used to characterize the spatial morphology and surface features of the target abandoned mine remediation area. It includes at least topographic elevation data, surface morphology data, and geographic reference data corresponding to the spatial segment range of the mine remediation area. The topographic elevation data is used to describe the spatial undulation of the surface in the mine area, the surface morphology data is used to describe the continuous distribution characteristics of the surface structure in the mine area, and the geographic reference data is used to provide a unified spatial coordinate benchmark. Based on the mine spatial basic dataset, a three-dimensional topographic surface model is constructed after performing coordinate unification processing on various types of data. The three-dimensional topographic surface model is a three-dimensional spatial model that continuously expresses the surface spatial morphology of the mine remediation area, and is used to provide a spatial bearing basis for subsequent engineering constraint loading, along-line sampling analysis, and segment object mapping. In the process of constructing the three-dimensional topographic surface model, techniques such as topographic data reconstruction, spatial interpolation, and surface continuity processing are used to transform discrete or semi-discrete topographic information into a continuous three-dimensional topographic surface that can be used for spatial analysis.

[0017] In this embodiment S1, the linear engineering planning constraint set is a pre-determined set of engineering constraints for the linear engineering projects to be implemented during the mine ecological restoration process. It includes at least slope constraints, continuity constraints, and spatial access constraints related to road engineering, drainage engineering, or other linear engineering projects. The linear engineering planning constraint set originates from the mine ecological restoration planning and design stage or engineering design specifications, and is used to limit the feasibility and rationality boundaries of the linear engineering projects within the mine remediation area. Loading the linear engineering planning constraint set into the three-dimensional terrain surface model is to establish the engineering constraints and actual terrain morphology in three-dimensional space. The correspondence between the linear engineering planning constraint set and the three-dimensional terrain surface model is established, enabling engineering constraints to directly participate in subsequent sampling analysis and segment constraint determination. The loading process maps the constraints in the linear engineering planning constraint set to the corresponding spatial locations of the three-dimensional terrain surface model through spatial mapping, coordinate association, or attribute binding. After the loading is completed, an engineering constraint interaction relationship is established between the linear engineering planning constraint set and the three-dimensional terrain surface model. The engineering constraint interaction relationship is used to characterize the correspondence between the terrain state and the engineering constraint conditions in a specific spatial location or segment, providing a basis for the subsequent construction of the minimum destruction unit object and the mutation event object.

[0018] In this embodiment S1, the mutation-dominated dynamic 3D model layer is constructed based on a 3D terrain surface model and superimposed with engineering constraint relationships. It is used to carry a 3D model layer that associates multiple engineering state evolution information under a unified 3D spatial benchmark. The mutation-dominated dynamic 3D model layer includes: a 3D terrain surface model constructed from a mine spatial basic dataset, engineering constraint relationships formed by loading a linear engineering planning constraint set, and minimum destruction unit objects and mutation event objects. Among them, the minimum destruction unit objects are mapped onto the 3D terrain surface model in the form of segments, and the mutation event objects are associated with the corresponding minimum destruction unit objects. This is used to represent the local engineering constraint state and its change results in the mutation-dominated dynamic 3D model layer.

[0019] In this embodiment S1, the unified three-dimensional spatial benchmark is a three-dimensional spatial reference benchmark used to consistently locate and associate various spatial data and engineering status information within the mine governance area. It is formed by performing coordinate unification processing on the mine spatial basic dataset, ensuring that the three-dimensional terrain surface model, linear engineering planning constraint set, and subsequently generated various engineering status objects are mapped and associated under the same three-dimensional spatial coordinate system. The unified three-dimensional spatial benchmark serves as the underlying spatial reference of the mutation-dominated dynamic three-dimensional model layer, avoiding spatial offset problems caused by different data sources and different engineering stages, and providing a spatial consistency basis for the unified carrying of various engineering status evolution information. The foundation; multiple engineering state evolution information is a set of engineering state information that changes during the analysis, verification, and write-back operations in the process of mine ecological restoration planning and linear engineering planning. It includes at least the surface space state reflected by the three-dimensional terrain surface model, the engineering constraint relationship state formed by loading the linear engineering planning constraint set, the segment constraint state corresponding to the minimum destruction unit object constructed along the engineering corridor direction, and the engineering constraint violation state represented by the mutation event object associated with the minimum destruction unit object. The multiple engineering state evolution information has different state values ​​at different planning stages, which are used to reflect the dynamic change process of the feasibility of linear engineering in the mine governance area.

[0020] In this embodiment S1, the mutation-dominated dynamic 3D model layer is used to centrally carry and manage the above-mentioned multiple engineering state evolution information under a unified 3D spatial reference. It establishes a segment-level and event-level object mapping structure on the 3D terrain surface model, so that engineering constraint relationships, minimum destruction unit objects, and mutation event objects can be associated and expressed in the same model layer. Among them, the minimum destruction unit object is mapped to the corresponding spatial position of the 3D terrain surface model in the form of a segment to carry the local engineering constraint state. The mutation event object is associated with the corresponding minimum destruction unit object to carry the engineering constraint violation state. Thus, the engineering state information at different levels forms an associative and updatable overall structure in the mutation-dominated dynamic 3D model layer.

[0021] In this embodiment S1, the data structure of the mutation-dominated dynamic 3D model layer is specifically as follows: a multi-layered associated data structure is constructed using a 3D terrain surface model as the spatial index, the smallest destruction unit object divided along the engineering corridor direction as the segment node, the mutation event object bound to the segment node as the event node, and an updatable engineering state field. This structure supports the identification, updating, and writing back of local engineering constraint states. The process of constructing the mutation-dominated dynamic 3D model layer based on the 3D terrain surface model and the linear engineering planning constraint set includes, after completing the construction of the 3D terrain surface model, loading the various engineering constraint conditions in the linear engineering planning constraint set into the 3D terrain surface model according to a unified 3D spatial benchmark, and establishing the engineering constraint interaction relationship through spatial mapping and attribute binding. On this basis, an object carrying structure is reserved in the mutation-dominated dynamic 3D model layer for writing the smallest destruction unit object and the mutation event object, so that the segment objects and event objects generated in subsequent steps can be directly written and associated with the corresponding spatial location and engineering constraint state, thereby completing the overall construction of the mutation-dominated dynamic 3D model layer.

[0022] In this embodiment S1, the technical means used in the construction of the mutation-driven dynamic three-dimensional model layer include at least the unified spatial coordinate processing technology, the three-dimensional terrain surface reconstruction technology, the engineering constraint spatial mapping technology, and the multi-object association modeling technology. Among them, the unified spatial coordinate processing technology is used to form a unified three-dimensional spatial reference, the three-dimensional terrain surface reconstruction technology is used to construct a continuous three-dimensional terrain surface model, the engineering constraint spatial mapping technology is used to load the linear engineering planning constraint set onto the three-dimensional terrain surface model and establish the engineering constraint interaction relationship, and the multi-object association modeling technology is used to establish the association structure between the three-dimensional terrain surface model, the engineering constraint interaction relationship, the minimum destruction unit object and the mutation event object within the same model layer, so as to support the dynamic update and write-back operation of the subsequent engineering state.

[0023] In this embodiment S2, the engineering constraint relationship is the spatial correspondence established between the engineering constraints in the linear engineering planning constraint set and the three-dimensional terrain surface model in the mutation-dominated dynamic three-dimensional model layer. It is used to characterize whether the terrain state in a specific spatial location or segment meets the constraint conditions in the linear engineering planning constraint set. The engineering constraint relationship is formed by loading the linear engineering planning constraint set onto the three-dimensional terrain surface model. Specifically, based on a unified three-dimensional spatial benchmark, each engineering constraint condition is mapped to the corresponding spatial location in the three-dimensional terrain surface model, and an engineering constraint status identifier is generated for the corresponding location or segment in the model layer. The engineering corridor direction is the predetermined or presumed engineering direction of the linear engineering in the mine ecological restoration plan. It is used to limit the sampling direction of the sampling change sequence along the line and the segment division direction of the minimum destruction unit object. The engineering corridor direction is determined according to the engineering layout information in the linear engineering planning constraint set, or according to the start and end positions of the linear engineering in the mine governance area and their spatial connection relationship, and serves as a directional reference for the analysis and segmentation processing along the line in the mutation-dominated dynamic three-dimensional model layer.

[0024] In this embodiment S2, the along-line sampling change sequence is a terrain change data sequence obtained by continuously sampling the three-dimensional terrain surface model in the mutation-dominated dynamic three-dimensional model layer based on the engineering constraint relationship and along the engineering corridor direction. It is used to characterize the continuous change state of the terrain spatial morphology in the engineering corridor direction, and is also used to compare and analyze with the engineering constraint relationship to identify the changes in the local engineering constraint state, so as to construct the minimum destruction unit object. The minimum destruction unit object is a segment unit divided along the engineering corridor direction, which is used to carry the engineering constraint state in the corresponding segment. The data structure of the minimum destruction unit object includes the segment spatial identifier, the along-line sampling change sequence segment corresponding to the segment, and the segment engineering constraint state field.

[0025] In this embodiment S2, the along-line sampling change sequence is a set of terrain change data sequences obtained by continuously sampling the three-dimensional terrain surface model in the mutation-dominated dynamic three-dimensional model layer along the engineering corridor direction. It includes at least the terrain elevation change sequence, the surface slope change sequence, and the spatial change sequence to reflect the local terrain undulation characteristics along the engineering corridor direction. Among them, the terrain elevation change sequence is used to characterize the continuous change of terrain height along the engineering corridor direction, the surface slope change sequence is used to characterize the change of terrain slope along the engineering corridor direction, and the spatial change sequence is used to help depict the abrupt changes in local terrain morphology. The along-line sampling change sequence is obtained by continuously sampling the three-dimensional terrain surface model along the engineering corridor direction in the mutation-dominated dynamic three-dimensional model layer. The continuous sampling is based on a unified three-dimensional spatial reference, and the three-dimensional terrain surface model is sampled point by point or segment by segment along the engineering corridor direction at predetermined spatial intervals. Techniques such as spatial interpolation, surface reconstruction, or rasterization are used to transform the terrain information of discrete sampling points into a continuous terrain change data sequence. The terrain change data sequence is the basic data reflecting the changes in terrain spatial morphology along the engineering corridor direction, which is formed into the along-line sampling change sequence after being serialized and organized.

[0026] In this embodiment S2, the comparative analysis between the sampling change sequence along the route and the engineering constraint relationship is as follows: In the mutation-dominated dynamic three-dimensional model layer, the terrain change data corresponding to the sampling change sequence along the route is compared with the engineering constraint conditions recorded in the engineering constraint relationship segment by segment to determine whether the terrain state in each sampling segment meets the constraint conditions of the linear engineering planning constraint set; in this comparative analysis process, the changes in the local engineering constraint state are identified based on the comparison results, wherein the changes in the local engineering constraint state indicate that the terrain state in a certain segment changes from meeting the engineering constraint conditions to not meeting the engineering constraint conditions, or from not meeting the engineering constraint conditions to meeting the engineering constraint conditions; based on the comparative analysis results of the sampling change sequence along the route and the engineering constraint relationship, the continuous spatial segments in the direction of the engineering corridor are divided, and a minimum destruction unit object is generated for each segment; the minimum destruction unit object is used to carry the engineering constraint state in the corresponding segment, which exists in the form of segment objects in the mutation-dominated dynamic three-dimensional model layer, and is associated with the corresponding position of the three-dimensional terrain surface model through the segment spatial identifier.

[0027] In this embodiment S2, the data structure of the minimum destruction unit object includes a segment spatial identifier, a corresponding along-line sampling change sequence fragment, a segment engineering constraint state field, and an identifier field for associating with mutation event objects, so that each minimum destruction unit object can independently record and update the engineering constraint state within its corresponding segment. The construction method of the minimum destruction unit object is as follows: after generating the along-line sampling change sequence along the engineering corridor direction in the mutation-dominated dynamic three-dimensional model layer, the constraint check segment for comparison analysis is determined according to the engineering constraint action relationship, and the along-line sampling change sequence is segmented according to the constraint check segment to obtain the along-line sampling change sequence fragment corresponding to the segment; based on the along-line sampling change sequence fragment corresponding to each segment and the engineering constraint state recorded in the engineering constraint action relationship, a segment-level comparison analysis is performed, and the segment engineering constraint state field is output; the minimum destruction unit object is generated based on the segment spatial identifier, the along-line sampling change sequence fragment corresponding to the segment, and the segment engineering constraint state field, and the minimum destruction unit object is written into the mutation-dominated dynamic three-dimensional model layer to complete the segment objectification.

[0028] In this embodiment S2, the mutation event object is an event identifier object generated based on the constraint violation correspondence between the minimum breaking unit object and the linear engineering planning constraint set. It is used to characterize the local engineering mutation situation in which engineering constraint violation occurs in the minimum breaking unit object. The data structure of the mutation event object includes the corresponding minimum breaking unit object identifier, the engineering constraint violation type identifier, and the mutation status field. The specific method for constructing the mutation event object is as follows: for each minimum breaking unit object, it is determined whether the sampling change sequence along the line in its corresponding segment violates the constraint conditions in the linear engineering planning constraint set, and when there is a constraint violation, a mutation event object is generated that is bound one-to-one with the minimum breaking unit object.

[0029] In this embodiment S2, the constraint violation correspondence between the minimum destruction unit object and the linear engineering planning constraint set is a correspondence used to characterize whether there is a violation between the section terrain state carried by the minimum destruction unit object and the constraint conditions in the linear engineering planning constraint set. It includes at least the correspondence mapping between the minimum destruction unit object identifier and the constraint condition identifier, the constraint check result of the sampled change sequence segment along the corresponding section, and the engineering constraint violation type identifier. The constraint violation correspondence is obtained by performing constraint checks on the sampled change sequence segment along the corresponding minimum destruction unit object, and is used to determine whether the minimum destruction unit object has an engineering constraint violation and to determine the nature of the violation. The corresponding engineering constraint violation type; the local engineering abruptness of engineering constraint violation in the minimum destruction unit object refers to the local engineering constraint state abruptness formed when the terrain change state reflected by the sampled change sequence fragments along the line does not meet at least one constraint condition in the linear engineering planning constraint set within the range of action defined by the minimum destruction unit object; the local engineering constraint state abruptness includes the state abruptness of continuous downhill constraint not being met within the section, the state abruptness of slope constraint not being met within the section, and the state abruptness of spatial access constraint not being met within the section. The local engineering constraint state abruptness is used to trigger the generation of the abruptness event object and serves as the source of the engineering constraint violation type identifier of the abruptness event object.

[0030] In this embodiment S2, the data structure of the mutation event object includes a corresponding minimum destruction unit object identifier, an engineering constraint violation type identifier, and a mutation state field. The minimum destruction unit object identifier is an identifier field used to uniquely associate the minimum destruction unit object that has experienced an engineering constraint violation. The engineering constraint violation type identifier is an identifier field used to identify the constraint violation type corresponding to the mutation event object. The mutation state field is a field used to record the current state of the mutation event object. After the mutation event object is generated, it is written into the mutation-dominated dynamic 3D model layer and associated with the corresponding minimum destruction unit object, so that the mutation-dominated dynamic 3D model layer can carry the event expression of local engineering constraint state mutation.

[0031] In this embodiment S2, the method for constructing mutation event objects involves determining whether the sampled change sequence fragments along the line within the corresponding segment of each minimum destruction unit object violate the constraints in the linear engineering planning constraint set. Specifically, this involves locating the corresponding sampled change sequence fragments along the line in the mutation-dominated dynamic 3D model layer based on the segment spatial identifier of the minimum destruction unit object, and extracting the constraint condition set corresponding to the segment based on the engineering constraint interaction relationship. Segment-level constraint checking is performed on the sampled change sequence fragments along the line to obtain constraint check results. The segment-level constraint checking includes segment checking for slope constraints, segment checking for continuous downhill constraints, and segment checking for spatial access constraints. When the constraint check results indicate that at least one constraint condition in the segment is not satisfied, a mutation event object corresponding to the minimum destruction unit object is generated and written into the mutation-dominated dynamic 3D model layer. Simultaneously, the constraint violation type corresponding to the unsatisfied constraint condition is written into the engineering constraint violation type identifier.

[0032] In this embodiment S2, the above-mentioned determination process is performed on each minimum destruction unit object because the minimum destruction unit object is a segment unit divided along the direction of the engineering corridor. It is the object that bears the constraint state of the segment engineering and serves as the segment boundary for constraint checking. By performing constraint checking on the minimum destruction unit object, the constraint checking results can be matched one-to-one with the segment spatial identifier to form a writable constraint violation correspondence, thereby supporting the objectified expression of the mutation event object and the subsequent processing flow. The mutation event object is bound one-to-one with the minimum destruction unit object because the mutation event object is used to characterize the local engineering constraint state mutation within the segment defined by the minimum destruction unit object. By binding them one-to-one, it can be ensured that the spatial affiliation of the mutation event object is consistent with the segment's scope of action, and the mutation event object can be located, extracted, and updated in subsequent steps based on the minimum destruction unit object.

[0033] In this embodiment S2, the segment check processing for slope constraints includes: extracting the topographic elevation change sequence corresponding to the segment from the segment spatial identifier of the minimum failure unit object along the line sampling change sequence, and determining the elevation difference between adjacent sampling positions within the segment and the corresponding distance difference along the line based on the topographic elevation change sequence, thereby obtaining the local slope change sequence corresponding to each sampling position within the segment; extracting segment slope constraint check parameters based on the local slope change sequence and comparing them with the slope constraint conditions in the linear engineering planning constraint set, and outputting the slope constraint check result, wherein the segment slope constraint check parameters include at least the segment maximum slope parameter, the segment minimum slope parameter, and the segment slope abrupt change segment identifier, and the slope constraint check result includes the slope constraint satisfaction identifier and the slope constraint violation identifier.

[0034] In this embodiment S2, the segment inspection process for continuous downhill constraint conditions includes: extracting the terrain elevation change sequence corresponding to the segment from the sampling change sequence along the line based on the segment spatial identifier of the minimum failure unit object, and determining the elevation difference sign sequence of adjacent sampling positions within the segment based on the terrain elevation change sequence to obtain the downhill continuity state sequence within the segment; identifying whether there is a state reversal position within the segment that changes from a downhill state to an uphill state based on the downhill continuity state sequence, and marking the sampling position corresponding to the state reversal position as a reverse slope position identifier; generating a continuous downhill constraint inspection result based on the reverse slope position identifier and comparing it with the continuous downhill constraint conditions in the linear engineering planning constraint set, outputting a continuous downhill constraint satisfaction identifier or a continuous downhill constraint violation identifier, and recording the segment position index field corresponding to the reverse slope position identifier when there is a continuous downhill constraint violation.

[0035] In this embodiment S2, the segment check processing of spatial access constraints includes: extracting constraint status identifiers corresponding to spatial access constraints within the segment action range of the minimum destruction unit object based on engineering constraint action relationships, and performing segment aggregation on the constraint status identifiers to obtain a segment access constraint status field; determining whether there is a passage prohibition state or a passage restriction state within the segment based on the segment access constraint status field, and generating a spatial access constraint check result, wherein the spatial access constraint check result includes a access constraint satisfaction identifier or an access constraint violation identifier; when there is an access constraint violation, writing the corresponding access constraint violation identifier into an engineering constraint violation type identifier and forming a pair with the minimum destruction unit. The constraint violation correspondence is identified by the image identifier; the section-level constraint check processing also includes the recording processing of changes in the constraint status of local engineering projects. The recording processing includes: jointly collecting the section slope constraint check results, continuous downhill constraint check results, and spatial access constraint check results of the same minimum failure unit object to obtain the section engineering constraint status field and write it into the minimum failure unit object; determining the changes in the local engineering constraint status based on the changes in the section engineering constraint status field, and generating a mutation event object when an engineering constraint violation occurs and writing it into the mutation-dominated dynamic 3D model layer, so that the mutation-dominated dynamic 3D model layer can carry the correspondence between the section engineering constraint status field and the mutation status field.

[0036] In this embodiment S3, the sampled change segment along the line is a sequence segment extracted from the sampled change sequence along the line that is consistent with the spatial identifier of the smallest destruction unit object segment corresponding to the mutation event object; the feasibility evidence package is a data set formed by structuring and aggregating the sampled change segments along the line according to the engineering constraint violation type of the mutation event object, which is used to represent the spatial morphological characteristics and constraint status information of the engineering constraint violation within the corresponding smallest destruction unit object segment; the method of structuring and aggregating the sampled change segments along the line to generate the feasibility evidence package is as follows: based on the engineering constraint violation type recorded in the mutation event object, extract the change sequence field corresponding to the constraint violation type from the sampled change segments along the line, and encapsulate the extracted change sequence field together with the segment spatial identifier and the engineering constraint violation type identifier to generate a feasibility evidence package that corresponds one-to-one with the mutation event object.

[0037] In this embodiment S3, the structured aggregation of the sampled change fragments along the route to generate a feasibility evidence package involves performing field extraction, field alignment, field merging, and field encapsulation on the change sequence fields corresponding to the engineering constraint violation types in the sampled change fragments along the route. This process transforms the original sampled change fragments along the route into a data set that can be directly invoked by the subsequent minimal intervention kernel object generation process. The structured aggregation employs techniques including fragment location extraction based on segment spatial identifiers, field filtering based on engineering constraint violation types, sequence alignment based on a unified three-dimensional spatial benchmark, and data organization based on object encapsulation. The segment location extraction technology based on segment spatial identifiers is used to locate the sampled change segments along the line corresponding to the mutation event object in the mutation-dominated dynamic 3D model layer. The field filtering technology based on engineering constraint violation type is used to extract the change sequence field corresponding to the engineering constraint violation type from the sampled change segments along the line. The sequence alignment technology based on unified 3D spatial benchmark is used to perform sampling position index consistency processing on the extracted change sequence field. The data organization technology based on object encapsulation is used to encapsulate the segment spatial identifier, engineering constraint violation type identifier and change sequence field together into a feasibility evidence package and write it into the mutation-dominated dynamic 3D model layer to form an evidence set that corresponds one-to-one with the mutation event object.

[0038] In this embodiment S3, the change sequence fields include at least a topographic elevation change sequence field, a surface slope change sequence field, and a spatial change sequence field. The field organization of the change sequence fields uses the sampling location index field as a unified master index, and a correspondence between the change sequence fields and the sampling location index field is established in the feasibility evidence package. The feasibility evidence package includes at least a segment spatial identifier, an engineering constraint violation type identifier, a sampling location index field, and a set of change sequence fields corresponding to the sampling location index field, so that the feasibility evidence package can be used in subsequent steps to generate a minimum intervention action kernel object consistent with the segment range.

[0039] In this embodiment S3, the minimum intervention action kernel object is a set of intervention action parameters generated for mutation event objects within the segment of the minimum destruction unit object, used to limit the engineering intervention actions to be performed within the segment; the method for generating the minimum intervention action kernel object by combining the sampled change fragment along the line with the linear engineering planning constraint set is as follows: based on the sampled change fragment along the line and the engineering constraint violation type recorded in the feasibility evidence package, the constraint condition parameters corresponding to the engineering constraint violation type in the linear engineering planning constraint set are extracted, and an intervention action parameter set corresponding to the constraint condition parameters is generated within the segment spatial identifier limit of the minimum destruction unit object, thereby forming a minimum intervention action kernel object that corresponds one-to-one with the minimum destruction unit object.

[0040] In this embodiment S3, the minimum intervention action kernel object is a set of intervention action parameters generated for abrupt event objects within the minimum destruction unit object segment. It is used to limit the engineering intervention actions to be performed within the segment. The engineering intervention actions are local processing actions that adjust the engineering constraint state of the segment according to the linear engineering planning constraint set. The minimum intervention action kernel object includes at least a segment spatial identifier, an intervention action parameter field corresponding to the engineering constraint violation type identifier, and a segment action limitation field for characterizing the scope of intervention. The intervention action parameter field is used to indicate the adjustment parameters for the terrain state or constraint state within the segment, and the segment action limitation field is used to limit the intervention action to only act on the spatial range corresponding to the segment spatial identifier. Performing engineering intervention actions based on the minimum intervention action kernel object includes performing parameterized adjustment processing on the sampled change segments along the line recorded in the feasibility evidence package within the segment spatial identifier limitation range of the minimum destruction unit object, and forming an adjusted segment constraint state set for subsequent local verification and judgment.

[0041] In this embodiment S3, the process of generating a minimum intervention action kernel object by combining the sampled change segments along the line with the linear engineering planning constraint set includes determining the engineering constraint violation type identifier based on the feasibility evidence package and extracting the corresponding change sequence field, extracting the constraint condition parameters corresponding to the engineering constraint violation type identifier based on the linear engineering planning constraint set, and generating intervention action parameter fields based on the constraint condition parameters. The intervention action parameter fields include at least a slope adjustment parameter field for constraining the slope state, a continuity adjustment parameter field for constraining the continuous downhill state, and a passage adjustment parameter field for constraining the spatial passage state, so that the minimum intervention action kernel object can generate a set of local intervention action parameters that satisfy different engineering constraint violation types under the constraints of the segment action limitation field.

[0042] In this embodiment S3, the slope adjustment parameter field is a parameter field used to adjust the slope constraint state within the segment's effective range defined by the minimum destruction unit object. It is generated based on the surface slope change sequence field recorded in the feasibility evidence package and the slope constraint conditions in the linear engineering planning constraint set. The slope adjustment parameter field includes at least the segment target slope parameter, the slope adjustment magnitude parameter, and the slope adjustment effective range parameter. The segment target slope parameter characterizes the adjusted target slope state within the segment, the slope adjustment magnitude parameter characterizes the difference range between the current slope state and the target slope state, and the slope adjustment... An interval parameter is used to limit slope adjustment to only the spatially identified area of ​​the segment corresponding to the minimum damage unit object; the continuity adjustment parameter field is a parameter field used to adjust the continuous downslope constraint state within the segment range defined by the minimum damage unit object, and it is generated based on the topographic elevation change sequence field recorded in the feasibility evidence package and the continuous downslope constraint check results; the continuity adjustment parameter field includes at least a reverse slope location index field, a continuity correction direction parameter, and a continuity correction range parameter, wherein the reverse slope location index field is used to identify the location where continuous damage occurs within the segment, and the continuity correction direction parameter is used to characterize The elevation change direction when correcting this location, and the continuity correction range parameter are used to limit the continuity correction to only the local sampling location range corresponding to the reverse slope location index field; the access adjustment parameter field is a parameter field used to adjust the spatial access constraint state within the segment range defined by the minimum destruction unit object, which is generated based on the spatial change sequence field recorded in the feasibility evidence package and the spatial access constraint conditions in the linear engineering planning constraint set; the access adjustment parameter field includes at least a access-restricted location identifier field, an access adjustment method parameter, and an access adjustment range parameter, wherein the access-restricted location identifier field... The system is used to identify locations within a section where access is restricted. The access adjustment method parameter characterizes the access status adjustment method performed at that location. The access adjustment range parameter limits the access adjustment to only apply within the spatial identifier range of the section corresponding to the minimum destruction unit object. The minimum intervention action kernel object is composed of slope adjustment parameter fields, continuity adjustment parameter fields, and access adjustment parameter fields. It establishes a one-to-one correspondence with the minimum destruction unit object through the section spatial identifier, enabling the minimum intervention action kernel object to generate corresponding intervention action parameter sets for different types of engineering constraint violations within the limited section range.

[0043] In this embodiment S3, the local intervention verification loop is a verification processing path limited to the range of action of the minimum destruction unit object segment, used to verify the constraint satisfaction of the minimum intervention action kernel object in the corresponding segment; the elimination status of the mutation event object is a status identifier used to characterize whether the corresponding mutation event object still has an engineering constraint violation; the method of performing local verification on the minimum intervention action kernel object to determine the elimination status of the mutation event object is as follows: within the range of the segment spatial identifier of the minimum destruction unit object, the intervention action parameters corresponding to the minimum intervention action kernel object are applied to the sampled change segment along the line, and the segment constraint status after application is re-determined according to the linear engineering planning constraint set. When the determination result shows that there is no longer an engineering constraint violation in the corresponding segment, the elimination status identifier of the mutation event object is generated.

[0044] In this embodiment S3, the local intervention verification loop includes: verification segment limitation rules determined based on the mutation event object, a verification input set determined based on the feasibility evidence package, and a verification path that generates a verification result set based on the association between the verification input set and the minimum intervention action kernel object; wherein, the verification segment limitation rules determined based on the mutation event object are a set of rules that limit the spatial segment range involved in the local intervention verification based on the minimum destruction unit object identifier and its segment spatial identifier recorded in the mutation event object, used to ensure that the verification process is only executed within the segment range corresponding to the mutation event object; the verification input set determined based on the feasibility evidence package is a set of rules that limit the spatial segment range involved in the local intervention verification based on the minimum destruction unit object identifier and its segment spatial identifier recorded in the mutation event object, used to ensure that the verification process is executed only within the segment range corresponding to the mutation event object; The data set extracted from the evidence package, consisting of the sampled change fragments along the line corresponding to the mutation event object, the sampling location index field, and the engineering constraint violation type identifier, is used as the input basis for the verification process. The verification path for generating the verification result set based on the association between the verification input set and the minimum intervention action kernel object is as follows: under the constraints of the verification section limitation rules, the intervention action parameters in the minimum intervention action kernel object are applied to the verification input set to form an adjusted sampled change fragment along the line, and the section engineering constraint state re-determination processing is performed on the adjusted sampled change fragment along the line according to the linear engineering planning constraint set, thereby generating and outputting the verification result set used to characterize the elimination state of the mutation event object.

[0045] In this embodiment S3, the local intervention verification loop is a verification processing path limited to the scope of action of the minimum destruction unit object segment. It is used to verify the constraint satisfaction of the minimum intervention action kernel object in the corresponding segment and output the elimination status of the mutation event object. The elimination status of the mutation event object is a status identifier used to characterize whether there is still an engineering constraint violation in the corresponding segment. It includes at least an elimination status satisfaction identifier and an elimination status non-satisfaction identifier. The local intervention verification loop includes at least a verification input acquisition process, a segment constraint status re-determination process, and an elimination status output process. The verification input acquisition process is used to acquire the minimum intervention action kernel object and its corresponding sampled change segment within the scope of the segment spatial identifier. The segment constraint status re-determination process is used to re-determine the segment constraint status after applying the intervention action parameters based on the linear engineering planning constraint set. The elimination status output process is used to generate the elimination status of the mutation event object based on the re-determination result and write it into the verification result set.

[0046] In this embodiment S3, the method for locally verifying the kernel object of the minimum intervention action to determine the elimination status of the mutation event object includes applying the intervention action parameter field in the kernel object of the minimum intervention action to the sampled change segment along the line to form an adjusted sampled change segment along the line within the segment spatial identifier limit of the minimum destruction unit object. Then, according to the linear engineering planning constraint set, the adjusted sampled change segment along the line is subjected to slope constraint check processing, continuous downhill constraint check processing, and spatial passage constraint check processing. When the joint check result of the above constraint check processing shows that there is no engineering constraint violation in the corresponding segment, the elimination status is satisfied and the flag is written into the verification result set. When the joint check result shows that there is still an engineering constraint violation in the corresponding segment, the elimination status is not satisfied and the flag is written into the verification result set.

[0047] In this embodiment S3, the segment constraint state re-determination processing in the local intervention verification loop includes performing slope constraint check processing, continuous downhill constraint check processing, and spatial access constraint check processing on the adjusted sampled change segments after applying the minimum intervention action kernel object within the segment spatial identifier limitation range of the minimum destruction unit object, and performing segment-level aggregation of the output results of each check processing; wherein, the slope constraint check processing is used to determine whether the adjusted segment slope state meets the slope constraint condition, the continuous downhill constraint check processing is used to determine whether the adjusted segment still has a reverse slope position identifier, and the spatial access constraint check processing is used to determine whether the adjusted segment still has a access restriction state; the determination of the elimination state of the mutation event object is performed based on the above segment-level aggregation results, when the slope constraint check processing and continuous downhill constraint check processing are performed, the determination of the elimination state of the mutation event object is performed based on the above segment-level aggregation results, when the slope constraint check processing and continuous downhill constraint check processing are performed, the determination of the elimination state of the mutation event object is performed based on the above segment-level aggregation results, and the determination of the elimination state of the mutation event object is performed based on the segment spatial identifier limitation range of the minimum destruction unit object. When the combined results of the processing and spatial access constraint check both indicate that there is no engineering constraint violation in the corresponding segment, an elimination state satisfaction flag is generated and used as the elimination state of the mutation event object; when at least one engineering constraint violation exists in the combined results, an elimination state dissatisfaction flag is generated and used as the elimination state of the mutation event object; the elimination state flag is associated with the corresponding minimum destruction unit object flag and mutation event object flag; the verification path of the local intervention verification loop is always limited to the segment spatial flag range of the minimum destruction unit object, so that the verification processing does not affect the engineering constraint state of adjacent segments, and ensures that the elimination state determination result of the mutation event object only reflects the engineering constraint change within the corresponding segment, thereby providing segment-level verification basis for subsequently writing the minimum intervention action kernel object back to the mutation-dominated dynamic 3D model layer.

[0048] In this embodiment S3, the verification result set is a set of verification data output from the local intervention verification loop, used to record the verification judgment results of each minimum intervention action kernel object within the range of action of the corresponding minimum destruction unit object segment. The data structure of the verification result set includes at least the minimum destruction unit object identifier, the mutation event object identifier, the minimum intervention action kernel object identifier, the elimination status identifier, and the segment constraint status re-judgment result field. The minimum destruction unit object identifier is used to locate the corresponding segment object, the mutation event object identifier is used to locate the corresponding event object, the minimum intervention action kernel object identifier is used to locate the corresponding intervention action parameter set, the elimination status identifier is used to characterize the elimination status of the mutation event object, and the segment constraint status re-judgment result field is used to record the joint judgment output of slope constraint check processing, continuous downhill constraint check processing, and spatial access constraint check processing. The verification result set is used as the input data set for write-back processing and feasibility status update processing to realize the status update and consistency maintenance of the minimum destruction unit object and mutation event object in the mutation-dominated dynamic three-dimensional model layer.

[0049] In this embodiment S4, the minimum intervention action kernel object corresponding to the verification result set is written back to the mutation-dominated dynamic three-dimensional model layer. Specifically, the minimum intervention action kernel object whose elimination state is satisfied in the verification result set is written into the mutation-dominated dynamic three-dimensional model layer, and the segment engineering constraint state field of the corresponding minimum destruction unit object and the mutation state field of the mutation event object are updated. Based on the updated mutation-dominated dynamic three-dimensional model layer, the linear engineering planning constraint set is parametrically reconstructed. Specifically, within the range of action of the minimum destruction unit object segment, the intervention action parameters corresponding to the written minimum intervention action kernel object are mapped to the engineering constraint parameter adjustment amount, and the engineering parameterized adjustment result corresponding one-to-one with the segment space identifier is formed, thereby generating the linear engineering planning dataset.

[0050] In this embodiment S4, the write-back process of writing back the minimum intervention action kernel object corresponding to the verification result set to the mutation-dominated dynamic 3D model layer is a model state update operation performed within the mutation-dominated dynamic 3D model layer. It filters the minimum intervention action kernel objects based on the elimination state identifier recorded in the verification result set, and only performs the write process on the minimum intervention action kernel objects whose elimination state identifier is satisfied. The write-back process includes writing the minimum intervention action kernel object to the corresponding segment position in the mutation-dominated dynamic 3D model layer, and synchronously updating the segment engineering constraint state field of the corresponding minimum destruction unit object and the mutation state field of the mutation event object, so that the state of each segment object and event object in the mutation-dominated dynamic 3D model layer is consistent with the verification result.

[0051] In this embodiment S4, the segment engineering constraint state field of the minimum disruptive unit object is updated to characterize the engineering constraint state of the corresponding segment after applying the minimum intervention action kernel object, and the mutation state field of the mutation event object is updated to characterize whether the corresponding mutation event object has been eliminated. Through the updating of the above state fields, the mutation-dominated dynamic three-dimensional model layer can reflect the latest engineering state of each segment after local intervention and verification, thereby forming an effective model state basis for subsequent planning reconstruction. Based on the updated mutation-dominated dynamic three-dimensional model layer, parametric reconstruction processing is performed on the linear engineering planning constraint set, which is a process of adjusting and reorganizing the parameters of the linear engineering planning constraints at the segment level. The parametric reconstruction processing includes extracting the intervention action parameters written in the minimum intervention action kernel object within the segment of the minimum disruptive unit object, and mapping the intervention action parameters to the engineering constraint parameter adjustment amount in the linear engineering planning constraint set, thereby updating the engineering constraints of local segments while keeping the overall linear engineering planning structure unchanged.

[0052] In this embodiment S4, the feasibility status of the minimum disruptive unit object is a status identifier used to characterize whether the segment corresponding to the minimum disruptive unit object meets the requirements of the linear engineering planning constraint set under the current planning and intervention conditions. It is determined based on the segment engineering constraint status field and is used to indicate whether the segment is in a feasible state that can be directly included in the linear engineering planning. When the segment corresponding to the minimum disruptive unit object meets all engineering constraints after applying the minimum intervention action kernel object and being verified by the local intervention verification loop, its feasibility status is marked as feasible. When the corresponding segment still has at least one engineering constraint violation, its feasibility status is marked as infeasible. The feasibility status of the mutation event object is a status identifier used to characterize whether the engineering constraint violation indicated by the mutation event object has been eliminated. It is determined based on the elimination status output by the local intervention verification loop and is used to indicate whether the corresponding local engineering mutation still constitutes a constraint on the linear engineering planning. When the segment corresponding to the mutation event object is verified to no longer have an engineering constraint violation after applying the minimum intervention action kernel object, its feasibility status is marked as eliminated. When the corresponding segment still has an engineering constraint violation, its feasibility status is marked as not eliminated.

[0053] In this embodiment S4, the adjustment amounts of engineering constraint parameters within the scope of action of each minimum damage unit object segment are aggregated at the segment level to form engineering parameterized adjustment results corresponding one-to-one with segment spatial identifiers. A linear engineering planning dataset is then generated based on the engineering parameterized adjustment results. The linear engineering planning dataset is a data set containing segment spatial identifiers, adjusted engineering constraint parameters, and segment engineering status identifiers, which is used to characterize the feasible planning status of linear engineering within the mine governance area. A mine ecological restoration planning scheme is generated based on the linear engineering planning dataset. Specifically, based on the segment engineering constraint parameters and engineering status identifiers recorded in the linear engineering planning dataset, a planning scheme is output for roads, drainage, and related linear engineering within the mine governance area, so that the generated mine ecological restoration planning scheme can meet the engineering constraint conditions at the segment level and has an implementation basis.

[0054] In this embodiment S4, the parametric reconstruction processing is an engineering constraint reconstruction method based on the state update results of the dynamic three-dimensional model layer dominated by mutation. It differs from the overall rerouting or global recalculation method. Instead, it performs local parameter mapping and adjustment within the scope of the smallest destruction unit object segment. By mapping the intervention action parameters in the smallest intervention action kernel object to the engineering constraint parameter adjustment amount, the linear engineering planning constraint set can achieve fine adjustment of the engineering conditions of local segments while maintaining the continuity of the overall structure. The generated linear engineering planning dataset serves as the direct data source for the mine ecological restoration planning scheme. It organizes the planning results through segment spatial identification, so that the planning scheme can be clearly mapped to the specific segment location within the mine governance area.

[0055] Example 2: The present invention proposes a mine ecological restoration planning system based on three-dimensional modeling, which is applied to the mine ecological restoration planning method based on three-dimensional modeling proposed in Example 1. It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the mine ecological restoration planning method based on three-dimensional modeling in Example 1.

[0056] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A mine ecological restoration planning method based on three-dimensional modeling, characterized in that, Includes the following steps: S1. Obtain the basic dataset of mine space and construct a three-dimensional terrain surface model. Load the linear engineering planning constraint set into the three-dimensional terrain surface model and establish the engineering constraint interaction relationship. Based on the three-dimensional terrain surface model and the linear engineering planning constraint set, construct a mutation-dominated dynamic three-dimensional model layer. S2. Based on the engineering constraint relationship and along the engineering corridor direction, generate the sampling change sequence along the line in the mutation-dominated dynamic three-dimensional model layer. Compare and analyze the sampling change sequence along the line with the engineering constraint relationship to construct the minimum destruction unit object, and generate the mutation event object corresponding to the minimum destruction unit object. Write the minimum destruction unit object and the mutation event object into the mutation-dominated dynamic three-dimensional model layer. In S2, the minimum destruction unit object is a segment unit divided along the engineering corridor direction to characterize the local terrain constraint state; the mutation event object is an event identifier object in the minimum destruction unit object that indicates an engineering constraint violation. S3. Extract the sampled change segments along the line located by the mutation event object from the mutation-dominated dynamic 3D model layer, and structure and collect the sampled change segments along the line to generate a feasibility evidence package. Combine the linear engineering planning constraint set to generate a minimum intervention action kernel object that corresponds one-to-one with the minimum destruction unit object. Based on the local intervention verification loop within the segment of the minimum destruction unit object, perform local verification on the minimum intervention action kernel object to determine the elimination status of the mutation event object, and output the verification result set. In S3, the minimum intervention action kernel object is a set of intervention actions used to eliminate the corresponding mutation event object within the segment range of the minimum destruction unit object; the local intervention verification loop is a verification path limited to the segment range of the minimum destruction unit object. S4. Write back the kernel object of the minimum intervention action corresponding to the verification result set to the mutation-dominated dynamic three-dimensional model layer, and update the feasibility status of the minimum destruction unit object and the mutation event object; based on the updated mutation-dominated dynamic three-dimensional model layer, parametrically reconstruct the linear engineering planning constraint set to obtain the linear engineering planning dataset, so as to generate a mine ecological restoration planning scheme.

2. The mine ecological restoration planning method based on three-dimensional modeling according to claim 1, characterized in that: In S1, the mutation-dominated dynamic 3D model layer is constructed based on a 3D terrain surface model and superimposed with engineering constraint relationships. It is used to carry a 3D model layer that associates multiple engineering state evolution information under a unified 3D spatial benchmark. The mutation-dominated dynamic 3D model layer includes: a 3D terrain surface model constructed from a mine spatial basic dataset, engineering constraint relationships formed by loading a linear engineering planning constraint set, as well as minimum destruction unit objects and mutation event objects. Among them, the minimum destruction unit objects are mapped onto the 3D terrain surface model in the form of segments, and the mutation event objects are associated with the corresponding minimum destruction unit objects. This is used to represent the local engineering constraint state and its change results in the mutation-dominated dynamic 3D model layer.

3. The mine ecological restoration planning method based on three-dimensional modeling according to claim 2, characterized in that: In S2, the along-line sampling change sequence is a terrain change data sequence obtained by continuously sampling the three-dimensional terrain surface model in the mutation-dominated dynamic three-dimensional model layer based on the engineering constraint relationship and along the engineering corridor direction. It is used to characterize the continuous change state of the terrain spatial morphology in the engineering corridor direction, and is also used to compare and analyze with the engineering constraint relationship to identify the changes in the local engineering constraint state, so as to construct the minimum destruction unit object. The minimum destruction unit object is a segment unit divided along the engineering corridor direction, which is used to carry the engineering constraint state in the corresponding segment. The data structure of the minimum destruction unit object includes the segment spatial identifier, the along-line sampling change sequence fragment corresponding to the segment, and the segment engineering constraint state field.

4. The mine ecological restoration planning method based on three-dimensional modeling according to claim 3, characterized in that: In S2, the mutation event object is an event identifier object generated based on the constraint violation correspondence between the minimum disruptive unit object and the linear engineering planning constraint set. It is used to characterize the local engineering mutation situation in which engineering constraint violation occurs in the minimum disruptive unit object. The data structure of the mutation event object includes the corresponding minimum disruptive unit object identifier, the engineering constraint violation type identifier, and the mutation status field. The specific method for constructing the mutation event object is as follows: for each minimum disruptive unit object, it is determined whether the sampling change sequence along the line in its corresponding segment violates the constraint conditions in the linear engineering planning constraint set, and when there is a constraint violation, a mutation event object is generated that is bound one-to-one with the minimum disruptive unit object.

5. The mine ecological restoration planning method based on three-dimensional modeling according to claim 4, characterized in that: In S3, the sampled change segment along the line is a sequence segment extracted from the sampled change sequence along the line that is consistent with the spatial identifier of the smallest destruction unit object segment corresponding to the mutation event object; the feasibility evidence package is a data set formed by structuring and aggregating the sampled change segments along the line according to the engineering constraint violation type of the mutation event object, which is used to represent the spatial morphological characteristics and constraint status information of the engineering constraint violation within the corresponding smallest destruction unit object segment; the method of structuring and aggregating the sampled change segments along the line to generate the feasibility evidence package is as follows: based on the engineering constraint violation type recorded in the mutation event object, extract the change sequence field corresponding to the constraint violation type from the sampled change segments along the line, and encapsulate the extracted change sequence field together with the segment spatial identifier and the engineering constraint violation type identifier to generate a feasibility evidence package that corresponds one-to-one with the mutation event object.

6. The mine ecological restoration planning method based on three-dimensional modeling according to claim 5, characterized in that: In S3, the minimum intervention action kernel object is a set of intervention action parameters generated for mutation event objects within the segment of the minimum destruction unit object, used to limit the engineering intervention actions to be performed within the segment. The method for generating the minimum intervention action kernel object by combining the sampled change fragments along the line with the linear engineering planning constraint set is as follows: based on the sampled change fragments along the line and the engineering constraint violation type recorded in the feasibility evidence package, the constraint condition parameters corresponding to the engineering constraint violation type in the linear engineering planning constraint set are extracted, and an intervention action parameter set corresponding to the constraint condition parameters is generated within the segment spatial identifier limit of the minimum destruction unit object, thereby forming a minimum intervention action kernel object that corresponds one-to-one with the minimum destruction unit object.

7. The mine ecological restoration planning method based on three-dimensional modeling according to claim 6, characterized in that: In S3, the local intervention verification loop is a verification processing path limited to the range of action of the minimum destruction unit object segment, used to verify the constraint satisfaction of the minimum intervention action kernel object in the corresponding segment; the elimination status of the mutation event object is a status identifier used to characterize whether the corresponding mutation event object still has an engineering constraint violation; the method of performing local verification on the minimum intervention action kernel object to determine the elimination status of the mutation event object is as follows: within the range of the segment spatial identifier of the minimum destruction unit object, the intervention action parameters corresponding to the minimum intervention action kernel object are applied to the sampled change segment along the line, and the constraint status of the applied segment is re-determined according to the linear engineering planning constraint set. When the determination result shows that there is no longer an engineering constraint violation in the corresponding segment, the elimination status identifier of the mutation event object is generated.

8. The mine ecological restoration planning method based on three-dimensional modeling according to claim 7, characterized in that: In step S4, the minimum intervention action kernel objects corresponding to the verification result set are written back to the mutation-dominated dynamic 3D model layer. Specifically, the minimum intervention action kernel objects whose elimination status is satisfied are written to the mutation-dominated dynamic 3D model layer, and the segment engineering constraint status field of the corresponding minimum destruction unit object and the mutation status field of the mutation event object are updated. Based on the updated mutation-dominated dynamic 3D model layer, the linear engineering planning constraint set is parametrically reconstructed. Specifically, within the range of action of the minimum destruction unit object segment, the intervention action parameters corresponding to the written minimum intervention action kernel objects are mapped to engineering constraint parameter adjustment amounts, and engineering parametric adjustment results corresponding one-to-one with the segment spatial identifiers are formed, thereby generating a linear engineering planning dataset.

9. A mine ecological restoration planning system based on three-dimensional modeling, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes a computer program to implement the mine ecological restoration planning method based on three-dimensional modeling as described in any one of claims 1-8.

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